KR20220070735A - Device for calculating focus of image and method thereof - Google Patents

Abstract

An image focus calculation device and method are provided. An image focus calculation device according to an embodiment of the present invention includes a memory for storing a focus calculation target image obtained from a camera, and a control part for calculating a focus value for the image stored in the memory. Here, the control part sets the size of an image window for focus calculation of the focus calculation target image, calculates a focus value in the image window for each pixel of the target image, and assigns a weight the focus value calculated in the image window for each pixel of the target image.

Description

Device for calculating focus of image and method thereof

The present invention relates to an image focus measurement operation and method, and more particularly, to an image focus measurement operation and method capable of accurately calculating an image focus through weight assignment through a variable window.

Existing image focus measurement operators have a fixed image window size. In this case, if the image window size is small, it is difficult to obtain an optimal image focus in a texture-free region in the image. In addition, if the image window size is large, blurring is caused when the 3D shape of the sample is restored.

In addition, since the existing image focus measurement operators assign constant weights to each focus value within a fixed image window, there is a problem in that the image focus operation accuracy used in the around-view system of the skid loader is lowered.

KR 2007-0050320 A

In order to solve the above problems of the prior art, an embodiment of the present invention is to provide an image focus calculation apparatus and method capable of accurately calculating an image focus through weight assignment through a variable window.

However, the problems to be solved by the present invention are not limited to the problems mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the following description.

According to an aspect of the present invention for solving the above problems, a memory for storing a focus operation target image obtained from a camera; and a control unit for calculating a focus value for the image stored in the memory, wherein the control unit sets a size of an image window for focus operation on the focus operation target image, and for each pixel of the target image, the An image focus operation apparatus is provided for calculating a focus value within an image window and assigning a weight to the calculated focus value within the image window to each pixel of the target image.

In an embodiment, the controller may remove noise of the weighted focus value within the image window with respect to each pixel of the target image.

In an embodiment, the controller may add the weighted focus values for each pixel of the target image within the image window.

In an embodiment, the controller may determine the size of the image window for the focus operation when the size of the image window is reduced while the size of the image window when the variance difference of brightness for each image window is smallest.

In an embodiment, the controller may apply a weight to the corresponding pixel according to a distance from another pixel in the image window.

In an embodiment, the controller may convert the target image into a gray level image.

In an embodiment, the control unit may calculate the focus value according to the following equation:

Here, ML(x,y) is the focal value of the corresponding pixel (x,y),

I(x,y) is the gray level brightness at that pixel (x,y).

In an embodiment, the control unit may allocate weights according to the following equation:

Here, AWML(x,y) is the weighted focus value for the pixel (x,y),

는 상기 설정된 영상 윈도우의 크기.

is the size of the set image window.

In an embodiment, the control unit may remove noise according to the following equation:

Here, ASWML(x,y) is the denoised focus value for the corresponding pixel (x,y).

According to another aspect of the present invention, the method comprising: setting a size of an image window for focus operation with respect to a focus operation target image; calculating a focus value within the image window for each pixel of the target image; and allocating a weight to the calculated focus value within the image window to each pixel of the target image.

In an embodiment, the image focus calculation method may further include removing noise of the weighted focus value within the image window with respect to each pixel of the target image.

In an embodiment, the removing of the noise may include summing the weighted focus values within the image window for each pixel of the target image.

In an embodiment, the step of setting the size of the image window decreases the size of the image window and sets the size of the image window when the variance difference in brightness for each image window is the smallest of the image window for the focus operation. size can be determined.

In an embodiment, the assigning of the weight may include applying the weight to the corresponding pixel according to a distance from another pixel in the image window.

In an embodiment, the image focus calculation method may further include converting the target image into a gray level image.

In an embodiment, the calculating of the focus value may include calculating the focus value according to the following equation:

Here, ML(x,y) is the focal value of the corresponding pixel (x, y),

I(x,y) is the gray level brightness at that pixel (x,y).

In one embodiment, the assigning the weight may assign the weight to the following equation:

Here, AWML(x,y) is the weighted focus value for the corresponding pixel (x,y),

는 상기 설정된 영상 윈도우의 크기.

is the size of the set image window.

In an embodiment, the removing of the noise may remove the noise according to the following equation:

Here, ASWML(x,y) is the denoised focus value for the corresponding pixel (x,y).

The image focus calculation apparatus and method according to an embodiment of the present invention can accurately calculate the image focus by setting the size of the image window variably and assigning an appropriate weight according to the distance from the central pixel in the image window, so that the image focus is reduced to image noise. It is robust and can improve the image focus operation accuracy.

1 is a block diagram of an image focusing apparatus according to an embodiment of the present invention.
FIG. 2 is a detailed block diagram of the control unit of FIG. 1 .
3 is a view for explaining the setting of a size of a variable window of an image focus operation apparatus according to an embodiment of the present invention.
4 is a diagram for explaining weight assignment of an image focus operation apparatus according to an embodiment of the present invention.
5 is a flowchart of an image focus calculation method according to an embodiment of the present invention.
6 is a flowchart of a window size setting procedure of FIG. 5 .

Hereinafter, with reference to the accompanying drawings, embodiments of the present invention will be described in detail so that those of ordinary skill in the art can easily carry out the present invention. The present invention may be embodied in many different forms and is not limited to the embodiments described herein. In order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and the same reference numerals are given to the same or similar components throughout the specification.

The embodiments of the present invention are provided to more completely explain the present invention to those of ordinary skill in the art, and the embodiments described below may be modified in various other forms, The scope is not limited to the following examples. Rather, these examples are provided so as to more fully and complete the present invention, and to fully convey the spirit of the present invention to those skilled in the art.

The terminology used herein is used to describe specific embodiments, not to limit the present invention. As used herein, the singular form may include the plural form unless the context clearly dictates otherwise. Also, as used herein, “comprise” and/or “comprising” refers to specifying the presence of the recited shapes, numbers, steps, actions, members, elements, and/or groups thereof. and does not exclude the presence or addition of one or more other shapes, numbers, movements, members, elements and/or groups. As used herein, the term “and/or” includes any one and all combinations of one or more of those listed items.

Although the terms first, second, etc. are used herein to describe various elements, regions and/or regions, it is to be understood that these elements, parts, regions, layers and/or regions are not limited by these terms. . These terms do not imply a specific order, upper and lower, or superiority, and are used only to distinguish one member, region or region from another member, region or region. Accordingly, a first member, region or region to be described below may refer to a second member, region or region without departing from the teachings of the present invention.

In this specification, terms such as “or”, “at least one” and the like may indicate one of the words listed together, or a combination of two or more. For example, "A or B" or "at least one of A and B" may include only one of A or B, or both A and B.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described with reference to drawings schematically illustrating embodiments of the present invention. In the drawings, variations of the illustrated shape may be expected, for example depending on manufacturing technology and/or tolerances. Therefore, the embodiment of the present invention should not be construed as limited to the specific shape of the region shown in this specification, but should include, for example, a shape change caused by manufacturing.

1 is a block diagram of an image focusing apparatus according to an embodiment of the present invention, and FIG. 2 is a detailed block diagram of the controller of FIG. 1 .

Referring to FIG. 1 , an image focus operation apparatus 100 according to an embodiment of the present invention may include a camera 110 , a controller 120 , and a memory 130 .

The image focus operation device 100 according to an embodiment of the present invention is to be applied to an around-view system of a skid loader, and variably sets the size of the image window by using the dispersion of the gray level image brightness within the image window, An optimal image focus may be obtained by allocating appropriate weights to neighboring pixels according to distances from the central pixel in the image window.

The camera 110 may be an around-view camera mounted on the skid loader. The camera 110 may take an image around the skid loader. For example, the camera 110 may acquire a gray level image in black and white. As another example, the camera 110 may acquire a color RGB image.

The memory 130 may store a focus operation target image obtained from the camera 110 . For example, the memory 130 may be a hard disk type, a magnetic media type, a compact disc read only memory (CD-ROM), or an optical media type depending on the type. , a magneto-optical media type, a multimedia card micro type, a flash memory type, a read only memory type, or a random access memory type) and the like, but is not limited thereto. In addition, the memory 130 may be a cache, a buffer, a main memory, an auxiliary memory, or a separately provided storage system according to its purpose/location, but is not limited thereto.

The controller 120 may be communicatively connected to the camera 110 and the memory 130 to control them. As an example, the controller 120 may include a processor that is hardware or a process that is software that is executed in a corresponding processor, but is not limited thereto.

The controller 120 may calculate a focus value for the image stored in the memory 130 . In this case, when the target image is not a gray level image such as an RGB image, the controller 120 may convert the target image into a gray level image.

Referring to FIG. 2 , the control unit 120 may include a window setting unit 122 , a focus value calculating unit 124 , a weight assigning unit 126 , and a noise removing unit 128 .

The window setting unit 122 may set the size of the image window for focus operation on the focus operation target image.

FIG. 3 is a view for explaining setting of a size of a variable window of an image focusing apparatus according to an embodiment of the present invention.

Referring to FIG. 3 , the window setting unit 122 reduces the size of the image windows W1 to W4 while focusing on the size of the image window when the variance difference in brightness for each image window W1 to W4 is smallest. It can be determined by the size of the image window for calculation. Here, the corresponding pixel (the central pixel) is indicated by a red dot. That is, the size of the image windows W1 to W4 with respect to the central pixel may vary.

In this case, the window setting unit 122 may set the initial image window size to a constant size (eg, 15×15) in order to variably set the image window size by using the dispersion of the gray level image brightness within the image window. In addition, the window setting unit 122 may reduce the size of the image window until the variance value of the gray level image brightness within the image window does not change, and select the size of the corresponding window as the size of the image window for focus operation.

For example, the window setting unit 122 may set 15 as the size Wi of the initial image window. Subsequently, the window setting unit 122 may decrease the size of the window by 1 to set the size Wn of the next image window to 14.

In this case, the window setting unit 122 may compare the initial image window and the next image window according to Equation 1 below.

Here, v _i and v _n are the variance values of the gray level image brightness for the initial image window and the next image window, respectively, and T is a size to a degree that it can be determined that the variance value does not change according to a change in the window size. It is a preset threshold.

That is, the window setting unit 122 may compare whether the absolute value of the variance difference between the gray level image brightness for the initial image window and the next image window exceeds the threshold value T. At this time, if the absolute value of the variance difference between the gray level image brightness for the initial image window and the next image window is greater than the threshold value T, the window setting unit 122 maintains the size Wi of the initial image window as it is. may decrease the size (Wn) of the next image window by 1.

Next, as described above, the window setting unit 122 may compare the variance values of the initial image window having a size of 15 and a next image window having a size of 13 as described above.

At this time, if the absolute value of the variance difference between the gray level image brightness for the initial image window and the next image window is less than or equal to the threshold value T, the window setting unit 122 may reduce the size Wi of the initial image window by 1. can That is, the window setting unit 122 may set the size Wi of the initial image window to 14.

Even in this case, the size Wn of the next image window may be decreased by 1 to be compared with the initial image window again. For example, the window setting unit 122 may compare an initial image window having a size of 14 with a next image window having a size of 13 .

As such, until the size Wn of the next image window is 1, the window setting unit 122 may compare the variance values while changing the sizes of the initial image window and the next image window. Here, the window setting unit 122 may select the size Wi of the final initial image window as the size of the image window for focus operation.

Accordingly, the image focus operation apparatus 100 according to an embodiment of the present invention can obtain an optimal image focus even in an area without a texture in the target image, and causes blurring when reconstructing a three-dimensional shape of the target image. You can set the video window to an appropriate size to avoid this.

Referring back to FIG. 2 , the focus value calculator 124 may calculate a focus value for each pixel of the target image within the image window. In this case, the focus value calculator 124 may calculate a focus value for each pixel according to Equation 2 below.

Here, ML(x,y) is the focus value of the corresponding pixel (x,y), and I(x,y) is the gray level brightness of the corresponding pixel (x,y). In addition, the corresponding pixel may be a central pixel within the image window. In this case, ML(x,y) may be understood as applying a Modified Laplacian (ML) operator to the central pixel (x,y).

The weight allocator 126 may allocate a weight to the focus value ML calculated within the image window to each pixel of the target image.

4 is a diagram for explaining weight assignment of an image focus operation apparatus according to an embodiment of the present invention.

Referring to FIG. 4 , in the image window W, weights may be assigned so that as the distance from the central pixel (red dot) increases, the influence on the central pixel is small, and the closer the distance from the central pixel (red dot) is, the greater the influence on the central pixel. .

In this case, the weight allocator 126 may apply a weight to the corresponding pixel (the central pixel; the red dot) according to a distance from other pixels in the image window W. Referring to FIG. For example, the weight allocator 126 may allocate a weight to the focus value ML according to Equation 3 below.

는 설정된 영상 윈도우의 크기이다. 이때, AWML(x,y)은 중심 픽셀(x,y)에서 AWML(Adaptive Weighted Modified Laplacian) 연산자를 적용한 것으로 이해될 수 있다.Here, AWML(x,y) is the weighted focus value for the pixel (x,y),

is the size of the set image window. In this case, AWML(x,y) may be understood as applying an Adaptive Weighted Modified Laplacian (AWML) operator to the central pixel (x,y).

That is, the weighted focus value AWML may be expressed as the sum of all pixels to which the weight is applied within the image window W centered on the corresponding pixel (x,y). In this case, the weight of each pixel may be determined according to a distance between the corresponding pixels within the image window W centered on the corresponding pixel (x, y).

Accordingly, the image focus operation apparatus 100 according to an embodiment of the present invention can be robust to image noise and improve image focus operation accuracy even when a separate noise removal process is not performed.

Referring back to FIG. 2 , the noise removing unit 128 may remove noise of a focus value AWML that is weighted within an image window with respect to each pixel of the target image. In this case, the noise removing unit 128 may sum the weighted focus values AWML for each pixel of the target image within the image window.

As an example, the noise removing unit 128 may remove noise of the focus value AWML to which a weight is applied according to Equation 4 below.

Here, ASWML(x,y) is the denoised focus value of the corresponding pixel (x,y). In this case, ASWML(x,y) may be understood as applying an Adaptive Sum of Weighted Modified Laplacian (ASWML) operator to the central pixel (x,y).

Accordingly, since the image focus operation apparatus 100 according to an embodiment of the present invention can accurately calculate the image focus, it is robust to image noise and improves the image focus operation accuracy.

Hereinafter, an image focus calculation method of the present invention will be described with reference to FIGS. 5 and 6 .

5 is a flowchart of an image focus calculation method according to an embodiment of the present invention.

The image focus calculation method 200 includes a window size setting step (S210), a focus value calculation step within the image window (S220), a weight assignment step (S230) to the focus value, and a noise removal step (S240) for the weighted focus value can do.

More specifically, as shown in FIG. 5 , first, the image focus operation apparatus 100 sets the size of an image window for focus operation on a focus operation target image (step S210 ). In this case, the image focus operation apparatus 100 may determine the size of the image window for the case where the variance difference of brightness for each image window is smallest as the size of the image window for the focus operation while reducing the size of the image window. A specific method will be described later with reference to FIG. 6 .

In this case, when the target image is not a gray level image, such as an RGB image, the image focusing apparatus 100 may convert the target image into a gray level image. Here, the gray level image conversion may be performed before setting the image window size.

Next, the image focus operation apparatus 100 calculates a focus value for each pixel of the target image within the image window (step S220 ). In this case, the image focus operation apparatus 100 may calculate a focus value ML for each pixel according to Equation 2 above.

Next, the image focus operation apparatus 100 allocates a weight to the focus value ML calculated within the image window to each pixel of the target image (step S230 ). Here, in the image window, weights may be assigned so that the farther the distance from the center pixel is, the smaller the effect on the center pixel is, and the closer the distance from the center pixel is, the greater the effect on the center pixel is.

In this case, the image focus operation apparatus 100 may apply a weight to the corresponding pixel according to a distance from another pixel in the image window. For example, the image focus operation apparatus 100 may assign a weight to the focus value ML according to Equation 3 above.

Here, the weighted focus value AWML may be expressed as the sum of all pixels to which the weight is applied in the image window centered on the corresponding pixel (x,y). In this case, the weight of each pixel may be determined according to the distance between the corresponding pixels in the image window centered on the corresponding pixel (x, y).

Accordingly, the image focus operation method 200 according to an embodiment of the present invention can be robust to image noise and improve image focus operation accuracy even when a separate noise removal process is not performed.

Next, the image focus operation apparatus 100 removes the noise of the weighted focus value AWML in the image window with respect to each pixel of the target image (step S240 ). In this case, the image focus operation apparatus 100 may sum the weighted focus values AWML for each pixel of the target image within the image window.

For example, the image focus operation apparatus 100 may remove noise from the focus value AWML to which a weight is applied according to Equation 4 above. Accordingly, the image focus operation apparatus 100 may finally calculate the noise-removed focus value ASWML.

Accordingly, since the image focus calculation method 200 according to an embodiment of the present invention can accurately calculate the image focus, it is robust to image noise and improves the image focus operation accuracy.

6 is a flowchart of a window size setting procedure of FIG. 5 .

The window size setting procedure 210 may include initial image window size setting steps ( S211 and S212 ) and determining the image window size according to the comparison of variance difference between the image windows ( S213 to S216 ).

In more detail, as shown in FIG. 6 , first, the image focus operation apparatus 100 sets the size of the initial image window to a constant size (step S211). For example, the image focus operation apparatus 100 may set the size Wn of the initial image window to 15. That is, the initial image window may have a size of 15×15.

Next, the image focus operation apparatus 100 sets the image window after the image window size is reduced (step S212). For example, the image focus operation apparatus 100 may decrease the size of the window by 1 and set the size Wn of the next image window to 14.

Next, the image focus operation device 100 determines whether a difference in brightness between the initial image window and the next image window is equal to or less than a threshold value T (step S213 ). Here, the brightness dispersion difference means the dispersion of the gray level image brightness within the image window.

For example, the image focus operation apparatus 100 may compare the initial image window and the next image window according to Equation 1 above. That is, the image focus operation apparatus 100 may compare whether the absolute value of the variance difference between the gray level image brightness for the initial image window and the next image window exceeds the threshold value T.

If it is determined in step S213 that the absolute value of the variance difference between the gray level image brightness for the initial image window and the next image window is greater than the threshold value T, the image focus operation apparatus 100 may return to step S212 .

In this case, the image focus operation apparatus 100 may decrease the size Wn of the next image window by 1 while maintaining the size Wi of the initial image window as it is. For example, the image focus operation apparatus 100 may repeat steps S212 to S213 to compare the injection values of the initial image window of 15 and the next image window of size 13.

As a result of the determination in step S213, if the absolute value of the variance difference between the gray level image brightness for the initial image window and the next image window is less than or equal to the threshold value T, the image focusing apparatus 100 determines the size of the initial image window (Wi) is decreased by 1 (step S214). As an example, the image focus operation apparatus 100 may set the size Wi of the initial image window to 14.

Next, the image focus operation device 100 determines whether the size of all image windows has been checked (step S215). have.

In this case, the image focus operation apparatus 100 may repeat steps S212 to S213 to decrease the size Wn of the next image window by 1 and compare it with the initial image window again. For example, the image focus operation apparatus 100 may compare an initial image window having a size of 14 with a next image window having a size of 13 .

As a result of the determination in step S215, if the size of all image windows is checked, the image focus operation device 100 finally determines the size of the current initial image window as the size of the image window for focus operation (step S216). ).

As such, the image focus operation device 100 reduces the size of the image window until the variance value of the gray level image brightness within the image window does not change, and selects the size of the corresponding window as the size of the image window for focus operation. have.

For example, the image focus operation apparatus 100 may compare the variance values while changing the sizes of the initial image window and the next image window until the size Wn of the next image window is 1. Here, the image focus operation apparatus 100 may select the size Wi of the final initial image window as the image window size for the focus operation.

Accordingly, the image focusing method 200 according to an embodiment of the present invention can obtain an optimal image focus even in an area without a texture in the target image, and does not cause blurring when reconstructing a three-dimensional shape of the target image. You can set the video window to a suitable size to avoid it.

The above methods may be implemented by the image focus computing device 100 as shown in FIG. 1 , and in particular, may be implemented as a software program for performing these steps, in this case, these programs are computer-readable It may be stored in a recording medium or transmitted by a computer data signal combined with a carrier wave in a transmission medium or a communication network. In this case, the computer-readable recording medium may include any type of recording device in which data readable by a computer system is stored. For example, it may be a ROM, RAM, CD-ROM, DVD-ROM, DVD-RAM, magnetic tape, floppy disk, hard disk, optical data storage device, and the like.

Although one embodiment of the present invention has been described above, the spirit of the present invention is not limited to the embodiments presented herein, and those skilled in the art who understand the spirit of the present invention can add components within the scope of the same spirit. , changes, deletions, additions, etc. will be able to easily suggest other embodiments, but this will also fall within the scope of the present invention.

100: image focus operation device 110: camera
120: control unit 122: window setting unit
124: focus value calculating unit 126: weight allocating unit
128: noise removing unit 130: memory

Claims (18)

a memory for storing a focus operation target image acquired by the camera; and
A control unit for calculating a focus value for the image stored in the memory,
The control unit is
Setting the size of the image window for focus operation on the focus operation target image,
For each pixel of the target image, a focus value is calculated within the image window;
An image focus calculation apparatus for allocating a weight to the calculated focus value within the image window, to each pixel of the target image. According to claim 1,
The control unit is configured to remove noise of the weighted focus value within the image window with respect to each pixel of the target image. 3. The method of claim 2,
The control unit is an image focus operation device for summing the weighted focus values in the image window with respect to each pixel of the target image. According to claim 1,
The control unit decreases the size of the image window and determines the size of the image window when the variance difference of brightness for each image window is smallest as the size of the image window for the focus operation. According to claim 1,
The control unit applies a weight to the corresponding pixel according to a distance from another pixel in the image window. According to claim 1,
The control unit converts the target image into a gray level image. According to claim 1,
The control unit is an image focus calculation device for calculating the focus value according to the following equation.

Here, ML(x,y) is the focal value of the corresponding pixel (x,y),
I(x,y) is the gray level brightness at that pixel (x,y) 8. The method of claim 7,
The control unit allocates weights according to the following equation.

Here, AWML(x,y) is the weighted focus value for the pixel (x,y),

is the size of the set image window 9. The method of claim 8,
The control unit is an image focus operation device for removing noise according to the following equation.

Here, ASWML(x,y) is the denoised focus value for the corresponding pixel (x,y) setting a size of an image window for focus operation on a focus operation target image;
calculating a focus value within the image window for each pixel of the target image; and
and assigning a weight to the calculated focus value within the image window to each pixel of the target image. 11. The method of claim 10,
The image focus operation method further comprising removing noise of the weighted focus value within the image window with respect to each pixel of the target image. 12. The method of claim 11,
The removing of the noise is an image focus calculation method of summing the weighted focus values within the image window with respect to each pixel of the target image. 11. The method of claim 10,
In the step of setting the size of the image window, the size of the image window is determined as the size of the image window for the focus operation when the size of the image window is reduced, and the difference in variance of brightness for each image window is smallest. How to calculate focus. 11. The method of claim 10,
The assigning of the weight is an image focus calculation method of applying a weight to a corresponding pixel according to a distance from another pixel in the image window. 11. The method of claim 10,
Image focus calculation method further comprising the step of converting the target image to a gray level image. 12. The method of claim 11,
The calculating of the focus value is an image focus calculation method of calculating the focus value according to the following equation.

Here, ML(x,y) is the focal value of the corresponding pixel (x, y),
I(x,y) is the gray level brightness at that pixel (x,y) 17. The method of claim 16,
The step of allocating the weight is an image focus calculation method of allocating a weight to the following equation.

Here, AWML(x,y) is the weighted focus value for the corresponding pixel (x,y),

is the size of the set image window 18. The method of claim 17,
The step of removing the noise is an image focus calculation method of removing the noise according to the following equation.

Here, ASWML(x,y) is the denoised focus value for the corresponding pixel (x,y)

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